Information processing apparatus, image delivery system, information processing method, and computer-readable recording medium

ABSTRACT

An information processing apparatus includes at least one processor configured to determine, on the basis of information concerning traveling of a vehicle obtained when an image is taken by an image pickup unit of the vehicle, a scene present when the image is taken; and transmit information indicating the determined scene and the image to a terminal connected to the information processing apparatus via a network.

CROSS-REFERENCE TO RELATED APPLICATION(S)

This application is a continuation of U.S. application Ser. No.16/266,473 filed Feb. 4, 2019, which is based on and claims priorityunder 35 U.S.C. 119 from Japanese Patent Application No. 2018-033527filed on Feb. 27, 2018. The contents of the above applications areincorporated herein by reference.

BACKGROUND OF THE INVENTION 1. Field of the Invention

The present invention relates to an information processing apparatus, animage delivery system, an information processing method, and acomputer-readable recording medium.

2. Description of the Related Art

According to the related art, an image taken (by photography) by atraveling vehicle is uploaded to a server; a scene at a place where theimage is taken is reported to a user who is remote from the place. Inthis regard, also according to the related art, in response to a requestfrom a user who is outside a vehicle, an image in the surroundings ofthe vehicle is uploaded to an image server that delivers the image tothe user (for example, see Japanese Laid-Open Patent Application No.2007-207260).

SUMMARY OF THE INVENTION

According to an embodiment of the present invention, an informationprocessing apparatus includes at least one processor configured todetermine, on the basis of information concerning traveling of a vehicleobtained when an image is taken by an image pickup unit of the vehicle,a scene present when the image is taken; and transmit informationindicating the determined scene and the image to a terminal connected tothe information processing apparatus via a network.

Other objects, features and advantages of the present invention willbecome more apparent from the following detailed description when readin conjunction with the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a configuration example of an image delivery systemaccording to an embodiment;

FIG. 2 illustrates a hardware configuration example of a serveraccording to the embodiment;

FIG. 3 is one example of a functional block diagram of the server and aterminal according to the embodiment;

FIG. 4 is a sequence diagram illustrating one example of processes ofthe image delivery system according to the embodiment;

FIG. 5 illustrates one example of image information according to theembodiment; and

FIG. 6 illustrates an example of a display screen of a terminal for auser to purchase an image or the like.

DETAILED DESCRIPTION OF THE EMBODIMENTS

In the related art described above, it may be difficult for a user toselect an image to be delivered from among a plurality of images.

An embodiment of the present invention has been devised in considerationof this point, and an object of the embodiment is to provide atechnology enabling a relatively easy selection of an image to bedelivered from among a plurality of images.

An information processing apparatus according to an embodiment of thepresent invention includes at least one processor configured todetermine, on the basis of information concerning traveling of a vehicleobtained when an image is taken (by photography) by an image pickup unitof the vehicle, a scene present when the image is taken; and transmitinformation indicating the determined scene and the image to a terminalconnected to the information processing apparatus via a network.

As a result, for example, a user can select an image to be delivered onthe basis of information indicating a scene. Accordingly, a user canrelatively easily select an image to be delivered from among a pluralityof images.

In an information processing apparatus according to another embodimentof the present invention, the information concerning traveling of thevehicle includes at least one of a traveling speed of the vehicle, anacceleration of the vehicle, information concerning a driver's drivingoperation of the vehicle, and information indicating actuating of apredetermined traveling function of the vehicle.

As a result, for example, a user can select an image to be delivered onthe basis of information indicating a scene determined on the basis ofinformation concerning traveling of the vehicle. Accordingly, a user canrelatively easily select an image to be delivered from among a pluralityof images.

In an information processing apparatus according to yet anotherembodiment of the present invention, the at least one processor isfurther configured to determine the scene present when the image istaken on the basis of a result of image recognition of the image andinformation of surroundings of the vehicle corresponding to a date andtime when the image is taken and a position where the image is taken.

As a result, for example, a user can select an image to be delivered onthe basis of information indicating a scene determined on the basis ofinformation of a disaster or the like occurring in the surroundings ofthe vehicle and an object detected from the image. Accordingly, a usercan relatively easily select an image to be delivered from among aplurality of images.

In an information processing apparatus according to yet anotherembodiment of the present invention, the at least one processor isfurther configured to decide a sales price of the image on the basis ofthe determined scene, and transmit, to the terminal, the image with theinformation indicating the determined scene and information indicatingthe sales price attached to the image.

As a result, for example, a user can purchase an image to be deliveredat a price decided on the basis of information indicating a scene.Accordingly, a user can relatively easily select an image to bedelivered from among a plurality of images, and also, can pay a pricecorresponding to a scene of the image to a user or the like who hasprovided the image.

In an information processing apparatus according to a yet anotherembodiment of the present invention, the at least one processor isfurther configured to decide the sales price on the basis of anoccurrence frequency of the determined scene.

As a result, for example, a user can purchase an image to be deliveredat a price decided on the basis of an occurrence frequency of a scene ofthe image. Accordingly, a user can relatively easily select an image tobe delivered from among a plurality of images, and also, can pay a pricecorresponding to an occurrence frequency of a scene of the image to auser or the like who has provided the image.

In an information processing apparatus according to a yet anotherembodiment of the present invention, the at least one processor isfurther configured to decide a higher sales price as a date and timewhen the image is taken is later or as a difference between the date andtime when the image is taken and a date and time when a predeterminedevent occurs at a position where the image is taken is smaller.

As a result, for example, a user can purchase an image to be deliveredat a price decided on the basis of date and time when the image istaken. Accordingly, a user can relatively easily select an image to bedelivered from among a plurality of images, and also, can pay a pricecorresponding to date and time when the image is taken to a user or thelike who has provided the image.

Other embodiments are implemented as an image delivery system, aninformation processing method, and a computer-readable recording medium.

According to the embodiments of the present invention, a user canrelatively easily select an image to be delivered from among a pluralityof images.

Below, an embodiment of the present invention will be described on thebasis of drawings.

<System Configuration>

FIG. 1 illustrates a configuration example of an image delivery systemaccording to the embodiment. In FIG. 1, the image delivery system 1includes a server 10, terminals 20-1 and 20-2 (hereinafter, for a casewhere the terminals need not be distinguished therebetween, each ofwhich will be simply referred to as a □terminal 20□), an in-vehicleapparatus 30 of a vehicle 301, and an external server 40. Note that thenumber of the terminals 20 is not limited to two.

The server 10 and each of the terminals 20, the in-vehicle apparatus 30,and the external server 40 are connected to perform communicationtherebetween through, for example, a network 50 such as the Internet, amobile telephone network, a wireless LAN (Local Area Network), a LAN, orthe like.

The in-vehicle apparatus 30 is, for example, an ECU (Electronic ControlUnit) or the like installed in the vehicle 301, and is connected to adrive recorder 60 (that is an example of an □image pickup unit□), acommunication apparatus, and so forth. The in-vehicle apparatus 30stores added information such as the speed, the position, and so forthof the vehicle 301 and a moving image taken (by photography) by thedrive recorder 60 in a recording medium such as a SD card, and uploadsthe added information and the moving image to the server 10.

The terminal 20 is, for example, an information processing apparatus(i.e., a computer) such as a smartphone, a tablet PC (PersonalComputer), or a notebook-size PC. A terminal 20 transmits a frameselected by the user from among frames of a moving image taken (byphotography) by the drive recorder 60 to the server 10. In addition, aterminal 20 purchases from the server 10 an image that is searched onthe basis of a tag indicated by the user from among a plurality ofimages uploaded to the server 10.

The server 10 is, for example, an information processing apparatus for aserver, and provides a service such as image delivery to a terminal 20.The server 10 attaches a tag to an image taken (by photography) by thevehicle 301 so that a terminal 20 can search for an image on the basisof a tag.

The external server 40 responds to a request from the server 10 todeliver to the server 10 information of the climate at a predetermineddate and time and place, information of a disaster (or an accident), orthe like.

<Hardware Configuration>

FIG. 2 illustrates a hardware configuration example of the server 10according to the embodiment. The server 10 of FIG. 2 includes a driveunit 100, an auxiliary storage unit 102, a memory unit 103, a CPU 104,an interface unit 105, and so forth that are connected with each otherby a bus B.

An information processing program to implement processes of the server10 is provided through, for example, a recording medium 101. In responseto setting of the recording medium 101 to the drive unit 100, theinformation processing program having been recorded in the recordingmedium 101, the information processing program is installed in theauxiliary storage unit 102 from the recording medium 101 via the driveunit 100. However, installing of the information processing program isnot necessarily implemented through the recording medium 101 and may bedownloaded from another computer via a network. The auxiliary storageunit 102 stores the installed information processing program, and alsostores necessary files, data, and so forth.

The memory unit 103 is, for example, a RAM (Random access memory), and,in response to an input of an instruction to start a program, reads theprogram from the auxiliary storage unit 102 and stores the program. TheCPU 104 implements functions of the server 10 according to the programstored in the memory unit 103. The interface unit 105 is used as aninterface to connect to a network.

Note that, examples of the recording medium 101 include portablerecording media such as a CD-ROM, a DVD, and a USB memory. Examples ofthe auxiliary storage unit 102 include a HDD (Hard Disk Drive), a flashmemory, and so forth. Each of the recording medium 101 and the auxiliarystorage unit 102 corresponds to a computer-readable recording medium.

Note that the hardware configurations of the terminals 20, thein-vehicle apparatus 30, and the external server 40 may be the same asor similar to the hardware configuration of the server 10.

<Functional Configuration>

Next, with reference to FIG. 3, functional configurations of theterminals 20 and the server 10 according to the embodiment will bedescribed. FIG. 3 is one example of a functional block diagram of theserver 10 and a terminal 20 according to the embodiment.

«Server 10»

The server 10 includes a storage part 11. The storage part 11 isimplemented by, for example, the auxiliary storage unit 102. The storagepart 11 stores image information 111 and so forth. Data included in theimage information 111 will be described later.

The server 10 further includes an obtaining part 12, a determinationpart 13, a decision part 14, a provision part 15, and a transmission andreception part 16. The obtaining part 12, the determination part 13, thedecision part 14, the provision part 15, and the transmission andreception part 16 represent functions implemented by processes performedby the CPU 104 of the server 10 according to one or more programsinstalled in the server 10.

The obtaining part 12 obtains an image that is taken by an image pickupunit (i.e., the drive recorder 60) of the in-vehicle apparatus 30, andobtains the date and time, position, and information concerningtraveling of the vehicle 301, in which the in-vehicle apparatus 30 isinstalled, at a time when the image is taken.

The determination part 13 determines, on the basis of informationconcerning traveling of the vehicle 301, a scene present when an imageis taken (by photography). In this regard, examples of a scene presentwhen an image is taken (by photography) include, for example, scenesconcerning driving and traveling of the vehicle 301 and scenesconcerning traffic such as an accident and a traffic jam occurring inthe surroundings of the vehicle 301. In addition, the determination part13 determines a scene present when an image is taken (by photography) onthe basis of the image obtained by the obtaining part 12 and informationof surroundings of the vehicle corresponding to the date and time andposition at which the image is taken.

The decision part 14 decides sales price of an image on the basis of ascene determined by the determination part 13 and so forth. The decisionpart 14 determines the sales price of an image, for example, on thebasis of the degree of rarity of the image, the degree of rarity of thescene, and so forth.

The provision part 15 sells an image to the user of a terminal 20 at asales price decided by the decision part 14. The provision part 15transmits an image and a tag corresponding to the image to the user of aterminal 20 who purchases the image.

The transmission and reception part 16 performs communication with aterminal 20, the in-vehicle apparatus 30, or the external server 40. Thetransmission and reception part 16 transmits, for example, an image withinformation indicating a scene determined by the determination part 13attached to the image to a terminal 20.

«Terminal 20»

Each of the terminals 20 includes a reception part 21, a control part22, and a transmission and reception part 23. These parts representfunctions implemented by processes performed by a CPU of the terminal 20according to one or more programs installed in the terminal 20.

The reception part 21 receives various operations performed by the user.The reception part 21 receives, for example, an operation performed bythe user to perform an adjustment on an image to be sold via the server10, a tag, and so forth. In addition, the reception part 21 receives,for example, an operation performed by the user to search for an imagesold via the server 10, an operation performed by the user to purchasethe image, and so forth.

The control part 22 performs, for example, a process to display, on thebasis of information received from the server 10, the information on adisplay screen. In addition, the control part 22 performs variousprocesses, for example, in response to the user's operations receivedvia the reception part 21.

The transmission and reception part 23 performs communication with theserver 10 according to an instruction that is input from the controlpart 22.

<Processes>

Next, with reference to FIGS. 4-6, processes of the image deliverysystem 1 according to the embodiment will be described. FIG. 4 is asequence diagram illustrating one example of processes of the imagedelivery system 1 according to the embodiment.

In step S1, the in-vehicle apparatus 30 stores an image (a moving imageor a static image) taken (by photography) and added information obtainedupon the taking of the image in a recording medium such as a SD card,and uploads the image and the added information to the server 10. Theadded information includes date and time information concerning the timeat which the image is taken, position information concerning theposition at which the image is taken, and information (i.e., vehicleinformation) concerning traveling of the vehicle 301 at the time whenthe image is taken. The position information may be, for example,information of a latitude and a longitude obtained from a GPS (GlobalPositioning System) or the like.

Information concerning traveling of the vehicle 301 includes the speedof the vehicle 301; the acceleration of the vehicle 301; drivingoperation information such as information concerning a driver's brakeoperation, a driver's steering operation, a driver's acceleratoroperation, and so forth; and information concerning actuating ofpredetermined traveling functions such as actuating of a function of anABS (Antilock Brake System) and a function of a TRC (TRaction Control)of the vehicle 301. The in-vehicle apparatus 30 may start taking themoving image, for example, in response to turning on of the ACC(accessory) power supply, and may upload the moving image taken (byphotography) to the server 10 in response to turning off of the ACCpower supply.

Note that in response to a detection of a predetermined event or inresponse to a satisfaction of a condition provided by the server 10, thein-vehicle apparatus 30 may upload the image to the server 10. Adetection of a predetermined event may be, for example, a detection ofone or more events included in the vehicle information such as adetection of a predetermined driver's operation such as a sudden brakingoperation or an abrupt steering operation, or a detection of anacceleration greater than or equal to a predetermined thresholdcorresponding to a collision of the vehicle 301 or the like. A conditionprovided by the server 10 may be, for example, a date and time, aposition, or the like indicated by the server 10.

Note that a terminal 20 may upload an image and added information of theimage to the server 10. In this case, for example, the terminal 20 mayread data of images from a recording medium such as a SD card whereimages taken (by photography) by the in-vehicle apparatus 30 arerecorded and may display the read images on a display screen, and mayupload an image selected from the displayed images and the correspondingadded information to the server 10.

Next, the determination part 13 of the server 10 performs an imagerecognition process on the image, obtained by the obtaining part 12, todetect a predetermined object from the image (step S2). Morespecifically, the determination part 13 of the server 10 detects fromthe image an object such as a pedestrian, a vehicle, a road cone, abicycle, a motorcycle, a traffic light, or a traffic sign. In a casewhere the image is a moving image, the determination part 13 of theserver 10 may perform the processes that will be described below on oneor more frames included in the moving image (for example, each key framenot compressed among frames).

Next, the obtaining part 12 of the server 10 obtains from the externalserver 40 information of surroundings of the vehicle 301 (hereinafter,referred to as □environmental information□ as appropriate), obtainedwhen the image is taken, corresponding to the date and time informationand the position information included in the added information (stepS3). The obtaining part 12 of the server 10 obtains, as theenvironmental information, climate information, traffic information,disaster information, and facility information obtained at the date andtime and position at which the image is taken. The climate informationmay include information such as information of the ambient temperature,the humidity, the weather, or a typhoon. The traffic information mayinclude information such as information of, for example, an accident, atraffic jam, or road construction work. The disaster information mayinclude, for example, information of an earthquake, falling of a bluff,a fire, a tsunami, or a flood. The facility information may includeinformation of, for example, a nearby store.

Next, the determination part 13 of the server 10 determines a scene(step S4). In this regard, the determination part 13 of the server 10uses, for example, AI (Artificial Intelligence) or the like to determinea scene present when the image is taken on the basis of at least one ofthe result of image recognition of the image obtained from step S2, theenvironmental information of the image obtained from step S3, and theadded information of the image.

The determination part 13 of the server 10 may determine, for example,that the scene is a scene of an □accident of a rear-end collision duringa standstill of the vehicle□, for a case where, on the basis of theinformation concerning traveling of the vehicle 301 included in theadded information, an acceleration greater than or equal to apredetermined threshold corresponding to a collision of the vehicle 301or the like is detected when a brake operation has been performed by thedriver of the vehicle 301 or the speed of the vehicle 301 has been zero.

The determination part 13 of the server 10 may determine, for example,that the scene is a scene of □a skid of the vehicle during traveling ofthe vehicle at a high speed□, for a case where, on the basis of theinformation concerning traveling of the vehicle 301, the speed of thevehicle 301 is greater than or equal to a predetermined threshold, theABS is actuated, and a brake operation is performed by the driver of thevehicle 301 with the strength greater than or equal to a predeterminedthreshold.

The determination part 13 of the server 10 may determine, for example,that the scene is a scene of □a collision accident due to a skid of thevehicle□, for a case where the ABS is actuated and an accelerationgreater than or equal to a predetermined threshold corresponding to acollision of the vehicle 301 or the like is detected.

The determination part 13 of the server 10 may determine, for example,that the scene is a scene of □a rear-end collision accident due todrowsy driving or the like□ for a case where the amount of a driver'ssteering operation is less than or equal to a predetermined threshold,the amount of a driver's brake operation is less than or equal to apredetermined threshold, and an acceleration greater than or equal to apredetermined threshold corresponding to a collision of the vehicle 301is detected.

Moreover, the determination part 13 of the server 10 may determine, forexample, that the scene is a scene of □an occurrence of an accident atthe traffic intersection A□, for a case where a traffic accident isdetected from image recognition and the image is taken at the trafficintersection A.

The determination part 13 of the server 10 may determine, for example,that the scene is a scene of □an occurrence of a skid due to roadsurface freezing at the traffic intersection A□, for a case where theambient temperature is minus 3 degrees according to the climateinformation included in the environmental information, the ABS isactuated according to the information concerning traveling of thevehicle 301 included in the added information, and a traffic accident isdetected from image recognition.

Moreover, the determination part 13 of the server 10 may determine, forexample, that the scene is a scene, for example, in which □there is aneed to wait for 30 minutes to enter the shop B□, for a case where aline of persons is detected from image recognition and the image istaken at the shop B.

The determination part 13 of the server 10 may determine, for example,that the scene is a scene, for example, in which □a lane restriction isimplemented at the address D due to construction work□, for a case whereconstruction work is detected from image recognition and the image istaken at the address D.

Next, the determination part 13 of the server 10 attaches, as a tag, theadded information of the image, information of the object obtained fromstep S2, the environmental information obtained from step S3, andinformation of the scene obtained from step S4, to the image (step S5).

Next, on the basis of the degree of rarity (the occurrence frequency) ofthe image and the degree of freshness of the image, the decision part 14of the server 10 decides an assessed price of a sales price (or a salesvalue) (step S6). In this regard, for example, the decision part 14 ofthe server 10 may decide a higher assessed price as the degree of rarityof the image and the degree of freshness of the image are higher. Notethat a sales price may be a money amount, or points exchangeable with apredetermined service or a predetermined product by the server 10.

The decision part 14 of the server 10 may determine, for example, thatthe degree of rarity of the image is higher as the number of imagesregistered as image information 111 that are similar to the image andcorrespond to positions included in a link (i.e., a road section)between two nodes (i.e., between two traffic intersections) in map datais smaller. In this case, the decision part 14 of the server 10 maydetermine that one image is similar to an other image for a case wherethe difference between an object and a scene detected from the one imageand an object and a scene detected from the other image is less than orequal to a predetermined threshold.

Moreover, the decision part 14 of the server 10 may determine the degreeof rarity of the image according to, for example, the scene of the imageand previously set degrees of rarity of various scenes. In this case,the decision part 14 of the server 10 determines, for example, that animage of an accident has the degree of rarity □10□ in a case where thepreviously set degree of rarity of a scene □an accident□ is □10□.

Moreover, the decision part 14 of the server 10 may determine, forexample, that the degree of freshness of the image is higher as the dateand time at which the image is taken is later. The decision part 14 ofthe server 10 may determine, for example, that the degree of freshnessof the image is higher as the difference between the date and time atwhich the image is taken and the date and time of an occurrence of anaccident (that is an example of an event) or a disaster (that is anotherexample of an event) such as an earthquake, falling of a bluff, a fire,a tsunami, or a flood, included in the environmental informationobtained from step S3 corresponding to the date and time at which theimage is taken, is smaller. As a result, for example, it is possible toset a higher sales price for an image that is the first report of anaccident or the like.

Moreover, the decision part 14 of the server 10 may decide the assessedprice of the sales price of the image according to, for example, thedegree of credibility of a user who provides the image. In this case,the decision part 14 of the server 10 may decide the degree ofcredibility for the user on the basis of, for example, the contents ofan adjustment performed by the user on an image of which the user hadpreviously permitted selling and a corresponding tag. For example, thedecision part 14 may set a higher degree of credibility for a user whoperformed an adjustment on an image to degrade the visibility ofpersonal information that had not been deleted in the image modified bythe server 10 or for a user who performed an adjustment on a taggenerated by the server 10 to improve the preciseness of the tag.

Next, the provision part 15 of the server 10 modifies the image forprotecting personal information or the like (step S7). In this regard,the provision part 15 of the server 10 may perform, for example, aprocess to pixelate a face of a person, a license plate, or the likeincluded in the image.

Next, the provision part 15 of the server 10 transmits the tag attachedto the image in step S5, the assessed price of the sales price of theimage determined in step S6, and the image modified in step S7 to theterminal 20-1 of the user of the in-vehicle apparatus 30 (step S8).

Next, the control part 22 of the terminal 20-1 displays on the displayscreen, the tag of the image, the sales price of the image, and themodified image (step S9).

Next, the reception part 21 of the terminal 20-1 receives the user'soperation to perform an adjustment on the tag, the sales price, and themodified image (step S10). Note that, in a case where the user of theterminal 20-1 determines not to perform such an adjustment, the user'soperation to perform an adjustment on the tag, the sales price, and themodified image is not needed.

Next, the control part 22 of the terminal 20-1 responds to the user'soperation to perform an adjustment on the tag, the sales price, and themodified image; and transmits to the server 10 the tag, the sales price,and the modified image on each of which the adjustment has beenperformed (step S11). Note that in response to receiving, if any, theuser's operation to deny selling the modified image, the control part 22of the terminal 20-1 sends information indicating the denial to theserver 10. Then, the provision part 15 of the server 10 deletes the dataconcerning the modified image selling which is thus denied.

Next, the provision part 15 of the server 10 permits selling themodified image to the other terminal 20-2 or the like (step S12). FIG. 5illustrates one example of image information 111 according to thepresent embodiment. In the example of the image information 111illustrated in FIG. 5, for an image for which the user of a terminal 20permits selling, the image, a tag, a sales price, and a user ID arestored where the image, tag, sales price, and user ID are associatedwith the image ID. An image ID is identification information to identifyan image taken (by photography) by the in-vehicle apparatus 30. An imageis an image taken (by photography) by the in-vehicle apparatus 30, amodified image obtained from step S7, or an image on which an adjustmentis performed in step S11. A □user ID□ is identification information toidentify a user who has uploaded an image to the server 10 from thein-vehicle apparatus 30 or the like.

Next, the provision part 15 of the server 10 responds to an operation ofthe user of the terminal 20-2 to transmit the image indicated by theuser, with the tag, the sales price, and so forth of the image to theterminal 20-2 (step S13). FIG. 6 illustrates an example of a displayscreen 601 of the terminal 20-2 with which the user of the terminal 20-2can purchase an image or the like. In the example of FIG. 6, on thedisplay screen 601 of the terminal 20-2, a thumbnail of an image 602, asales price 603, a tag 604, a □purchase□ button 605, and so forth aredisplayed. The provision part 15 of the server 10 responds to a pressingoperation of the user of the terminal 20-2 on the purchase button 605 totransmit the image concerning the thumbnail 602 and the tag of the imageto the terminal 20-2. Note that the terminal 20-2 may be able topreviously register with the server 10 a search condition for an image.In this case, in response to the image that satisfies the registeredcondition becoming purchasable, the provision part 15 of the server 10may send this information to the terminal 20-2.

Note that the server 10 may send information indicating a selling resultof an image that has been uploaded by the user of the terminal 20-1 at apredetermined timing (for example, every month) to the terminal 20-1.

Thus, the information processing apparatus, the image delivery system,the information processing method, and the computer-readable recordingmedium have been described as the illustrative embodiments. In thisregard, the present invention is not limited to the specificallydisclosed embodiments, and various modifications and/or changes may bemade within the claimed scope.

The functional parts of the terminals 20 and the server 10 may beimplemented, for example, through cloud computing using one or morecomputers. In addition, at least some of the functions of a terminal 20may be included in the server 10. In addition, at least some of thefunctions of the server 10 may be included in a terminal 20. Note that,in the embodiment, the server 10 is one example of an □informationprocessing apparatus□, and the provision part 15 is one example of afunction □to transmit information and an image□.

DESCRIPTION OF REFERENCE NUMERALS

-   1: image delivery system-   10: server-   11: storage part-   12: obtaining part-   13: determination part-   14: decision part-   15: provision part-   16: transmission and reception part-   20: terminal-   21: reception part-   22: control part-   23: transmission and reception part-   30: in-vehicle apparatus-   40: external server-   301: vehicle

The present application is based on and claims priority to Japanesepatent application No. 2018-033527, filed Feb. 27, 2018, the entirecontents of which are hereby incorporated herein by reference.

What is claimed is:
 1. An information processing apparatus comprising:at least one processor configured to: determine, based on informationconcerning traveling of a vehicle obtained when an image includingsurroundings of the vehicle is taken, a scene present in thesurroundings of the vehicle; set a sales price of the image based on thedetermined scene; and transmit, to a terminal, the image, informationindicating the determined scene, and the sales price.
 2. The informationprocessing apparatus as claimed in claim 1, wherein the informationconcerning traveling of the vehicle includes at least one of a travelingspeed of the vehicle, an acceleration of the vehicle, informationconcerning a driver's driving operation of the vehicle, and informationindicating actuating of a predetermined traveling function of thevehicle.
 3. The information processing apparatus as claimed in claim 1,wherein the at least one processor is further configured to: determinethe scene is present when the image is taken based on a result of imagerecognition of the image and information of the surroundings of thevehicle corresponding to a date and time when the image is taken and aposition where the image is taken.
 4. The information processingapparatus as claimed in claim 2, wherein the at least one processor isfurther configured to: determine the scene is present when the image istaken based on a result of image recognition of the image andinformation of the surroundings of the vehicle corresponding to a dateand time when the image is taken and a position where the image istaken.
 5. The information processing apparatus as claimed in claim 1,wherein the at least one processor is further configured to: set thesales price based on an occurrence frequency of the determined scene. 6.The information processing apparatus as claimed in claim 2, wherein theat least one processor is further configured to: set the sales pricebased on an occurrence frequency of the determined scene.
 7. Theinformation processing apparatus as claimed in claim 3, wherein the atleast one processor is further configured to: set the sales price basedon an occurrence frequency of the determined scene.
 8. The informationprocessing apparatus as claimed in claim 4, wherein the at least oneprocessor is further configured to: set the sales price based on anoccurrence frequency of the determined scene.
 9. The informationprocessing apparatus as claimed in claim 1, wherein the at least oneprocessor is further configured to: determine a difference between thedate and time when the image is taken and a date and time when apredetermined event occurs at a position where the image is taken; andset the sales price such that the sales price increases as thedetermined difference decreases.
 10. The information processingapparatus as claimed in claim 2, wherein the at least one processor isfurther configured to: determine a difference between the date and timewhen the image is taken and a date and time when a predetermined eventoccurs at a position where the image is taken; and set the sales pricesuch that the sales price increases as the determined differencedecreases.
 11. The information processing apparatus as claimed in claim3, wherein the at least one processor is further configured to:determine a difference between the date and time when the image is takenand a date and time when a predetermined event occurs at a positionwhere the image is taken; and set the sales price such that the salesprice increases as the determined difference decreases.
 12. Theinformation processing apparatus as claimed in claim 4, wherein the atleast one processor is further configured to: determine a differencebetween the date and time when the image is taken and a date and timewhen a predetermined event occurs at a position where the image istaken; and set the sales price such that the sales price increases asthe determined difference decreases.
 13. An image delivery systemcomprising: a vehicle; and an information processing apparatus, whereinthe vehicle transmits an image including surroundings of the vehicle andinformation concerning traveling of the vehicle obtained when the imageis taken to the information processing apparatus, and the informationprocessing apparatus includes at least one processor configured to:determine, based on the information concerning traveling of the vehicleobtained when the image is taken, a scene present in the surroundings ofthe vehicle; set a sales price of the image based on the determinedscene; and transmit, to a terminal, the image, information indicatingthe determined scene, and the sales price.
 14. The image delivery systemas claimed in claim 13, wherein the information concerning traveling ofthe vehicle includes at least one of a traveling speed of the vehicle,an acceleration of the vehicle, information concerning a driver'sdriving operation of the vehicle, and information indicating actuatingof a predetermined traveling function of the vehicle.
 15. The imagedelivery system as claimed in claim 13, wherein the at least oneprocessor is further configured to: determine the scene is present whenthe image is taken based on a result of image recognition of the imageand information of the surroundings of the vehicle corresponding to adate and time when the image is taken and a position where the image istaken.
 16. The image delivery system as claimed in claim 14, wherein theat least one processor is further configured to: determine the scene ispresent when the image is taken based on a result of image recognitionof the image and information of the surroundings of the vehiclecorresponding to a date and time when the image is taken and a positionwhere the image is taken.
 17. An information processing methodimplemented by an information processing apparatus, the informationprocessing method comprising: determining, by at least one processor ofthe information processing apparatus, based on information concerningtraveling of a vehicle obtained when an image including surroundings ofthe vehicle is taken, a scene present in the surroundings of thevehicle; setting a sales price of the image based on the determinedscene; and transmitting, to a terminal, the image, informationindicating the determined scene, and the sales price.
 18. Theinformation processing method as claimed in claim 17, wherein theinformation concerning traveling of the vehicle includes at least one ofa traveling speed of the vehicle, an acceleration of the vehicle,information concerning a driver's driving operation of the vehicle, andinformation indicating actuating of a predetermined traveling functionof the vehicle.
 19. The information processing method as claimed inclaim 17, wherein the information processing method further comprises:determining the scene is present when the image is taken based on aresult of image recognition of the image and information of thesurroundings of the vehicle corresponding to a date and time when theimage is taken and a position where the image is taken.
 20. Theinformation processing method as claimed in claim 18, wherein theinformation processing method further comprises: determining the sceneis present when the image is taken based on a result of imagerecognition of the image and information of the surroundings of thevehicle corresponding to a date and time when the image is taken and aposition where the image is taken.